Graphs of MCR vs Methane Production Relationship

This report looks at the relationship between MCR genes and Adjusted Total Methane Production

library(knitr)
library(plyr)
library(scales) #For formating values in graphs
library(RColorBrewer)
library(grid) #For graphing
library(ggplot2) #For graphing
# library(mgcv, quietly=TRUE) #For the Generalized Additive Model that smooths the longitudinal graphs.
#####################################

options(show.signif.stars=F) #Turn off the annotations on p-values
options(stringsAsFactors=FALSE) #By default, character/string variables will NOT be automatically converted to factors.

pathInputLong <- "./Data/Derived/AllBasinsLong.csv"
pathInputWide <- "./Data/Derived/AllBasinsWide.csv"

basinOrder <- c("Illinois Basin", "Cook Inlet gas field", "Powder River Basin")
substrateOrder <- c("Formate", "Acetate", "Propionate", "Butyrate", "Valerate")
sitesToDrop <- c(7, 16, 17)

ReportTheme <- theme_bw() +
  theme(axis.ticks = element_blank()) +
  theme(axis.text = element_text(color="gray10")) +
  theme(axis.title = element_text(color="gray10")) +
  theme(panel.border = element_rect(color="gray80")) +
  theme(strip.text = element_text(color="gray5")) +
  theme(strip.background=element_rect(color=NA, fill="gray97"))
#####################################

# 'ds' stands for 'datasets'
dsLong <- read.csv(pathInputLong)
dsWide <- read.csv(pathInputWide)
# sapply(dsWide, class)

#####################################

#Drop the sites without microarray data
dsLong <- dsLong[!(dsLong$Site %in% sitesToDrop), ]
dsWide <- dsWide[!(dsWide$Site %in% sitesToDrop), ]

#Reorder the substrates and basins.  The default alphabetical order isn't the most intuitive
dsLong$Basin <- factor(dsLong$Basin, levels=basinOrder)
dsWide$Basin <- factor(dsWide$Basin, levels=basinOrder)
dsLong$Substrate <- factor(dsLong$Substrate, levels=substrateOrder)
dsWide$Substrate <- factor(dsWide$Substrate, levels=substrateOrder)

dsLongIllinois <- dsLong[dsLong$Basin=="Illinois Basin", ]
dsWideIllinois <- dsWide[dsWide$Basin=="Illinois Basin", ]

CalculateSiteRange <- function( d ) {
  data.frame(
    RateMin = min(d$AdjustedRate, na.rm=T),
    RateMax = max(d$AdjustedRate, na.rm=T),
    TotalAdjustedMin = min(d$TotalAdjusted, na.rm=T),
    TotalAdjustedMax = max(d$TotalAdjusted, na.rm=T),
    UniqueMcrGenesMin = min(d$UniqueMcrGenes, na.rm=T),
    UniqueMcrGenesMax = max(d$UniqueMcrGenes, na.rm=T),
    QuantityMcrGenesMin = min(d$QuantityMcrGenes, na.rm=T),
    QuantityMcrGenesMax = max(d$QuantityMcrGenes, na.rm=T)
  )
}
dsSiteRange <- plyr::ddply(.data=dsLong, .variables=c("Basin", "Site", "Substrate"), CalculateSiteRange)

dsCorrelation <- plyr::ddply(dsWide, c("Basin", "Substrate"), summarize, 
                             CorrRateUnique=cor(RateMean, UniqueMean, use="pairwise.complete.obs"),
                             CorrRateQuantity=cor(RateMean, QuantityMean, use="pairwise.complete.obs"), 
                             CorrTotalUnique=cor(TotalAdjustedMean, UniqueMean, use="pairwise.complete.obs"),
                             CorrTotalQuantity=cor(TotalAdjustedMean, QuantityMean, use="pairwise.complete.obs"))
dsCorrelation$CorrRateUniquePretty <- paste0("italic(r)==", round(dsCorrelation$CorrRateUnique, 2))
dsCorrelation$CorrRateQuantityPretty <- paste0("italic(r)==", round(dsCorrelation$CorrRateQuantity, 2))
dsCorrelation$CorrTotalUniquePretty <- paste0("italic(r)==", round(dsCorrelation$CorrTotalUnique, 2))
dsCorrelation$CorrTotalQuantityPretty <- paste0("italic(r)==", round(dsCorrelation$CorrTotalQuantity, 2))

sitesIllinois <- sort(unique(dsLong[dsLong$Basin=="Illinois Basin", "Site"]))
sitesCook <- sort(unique(dsLong[dsLong$Basin=="Cook Inlet gas field", "Site"]))
sitesPowder <- sort(unique(dsLong[dsLong$Basin=="Powder River Basin", "Site"]))

paletteSiteDark <- c(RColorBrewer::brewer.pal(n=length(sitesIllinois), "Dark2"), RColorBrewer::brewer.pal(n=length(sitesCook), "Set1"), RColorBrewer::brewer.pal(n=length(sitesPowder), "Dark2"))
names(paletteSiteDark) <- c(sitesIllinois, sitesCook, sitesPowder)

paletteSiteLight <- grDevices::adjustcolor(paletteSiteDark, alpha.f=.5)
names(paletteSiteLight) <- c(sitesIllinois, sitesCook, sitesPowder)

#####################################

Notes

Marginals

ggplot(dsLongIllinois, aes(x=TotalAdjusted)) + 
  geom_density() +
  facet_grid(Substrate~IncubationReplicate, scales="free_y") +
  ReportTheme +
  labs(title="Illinois Basin")

ggplot(dsLongIllinois, aes(x=AdjustedRate)) + 
  geom_density() +
  facet_grid(Substrate~IncubationReplicate, scales="free_y") +
  ReportTheme +
  labs(title="Illinois Basin")

ggplot(dsLongIllinois, aes(x=QuantityMcrGenes)) + 
  geom_density() +
  facet_grid(Substrate~MicroarraryReplicate, scales="free_y") +
  ReportTheme +
  labs(title="Illinois Basin")

ggplot(dsLongIllinois, aes(x=UniqueMcrGenes)) + 
  geom_density() +
  facet_grid(Substrate~MicroarraryReplicate, scales="free_y") +
  ReportTheme +
  labs(title="Illinois Basin")

#####################################

Scatterplots

The first pair scatterplot matrices are for the quantity of genes, while the second pair is the count of unique genes. Within each pair, the first scatterplot matrix has all replicates (2 incubation and 3 microarray replications per site), while the second within each pair shows a site's average across the replicates.

The these scatterplots combine the site means, with the individual replicate measurements. The rectangles show the range for each Substrate-by-Site group of measurements. In these two graphs, the total methane produced is shown.

In these two graphs, the rate of methane produced is shown.

Questions

Unanswered Questions

1. - - -

Answered Questions

1. - - -

Session Information

For the sake of documentation and reproducibility, the current report was build on a system using the following software.

Report created by wibeasley at 2017-02-25, 00:11 -0600

R version 3.3.1 (2016-06-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.2 LTS

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggplot2_2.2.1      RColorBrewer_1.1-2 scales_0.4.1       plyr_1.8.4         knitr_1.15.1      

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.9      assertthat_0.1   gtable_0.2.0     magrittr_1.5     evaluate_0.10    highr_0.6       
 [7] stringi_1.1.2    reshape2_1.4.2   lazyeval_0.2.0   labeling_0.3     tools_3.3.1      stringr_1.2.0   
[13] munsell_0.4.3    colorspace_1.3-2 tibble_1.2